Artificial Intelligence is far from a new concept. Whether you’re familiar with Rosie from the Jetsons, R2-D2, or a doomsday scenario like The Matrix or Terminator, pop culture has proliferated AI for some time now. And while many of us associate AI with the examples as mentioned above as futuristic, the reality of AI is that it already infiltrates many aspects of our lives. And while Apple’s Siri and Amazon’s Alexa are typical examples, the truth is a growing number of businesses are becoming highly invested in AI as they attempt to utilize big data. Mortgage companies are no exception, as many are determining how AI can be implemented to offer a better mortgage solution.
One specific type of artificial intelligence that businesses already use to streamline operations and drive efficiency is machine learning. Machine learning involves building algorithms into computer programs, allowing machines to learn and adapt to new data without human interference. These sophisticated algorithms empower machines to process troves of data sets to make predictions based on previously analyzed data.
The benefit of machine learning to businesses large and small is the removal of tedious manual processes performed by humans. With machines able to produce a specific output based on large volumes of data, people are merely responsible for analyzing the results.
Specifically, in the mortgage industry, it is becoming entirely feasible for machines to assist in the processing of a mortgage application; to synthesize large data sets to determine the qualifications of a borrower.
Currently, several mortgage companies use machine learning technology to assist in the mortgage process. Examples include Experian which is using AI to learn from datasets what is most important during the application process. As explained by CIO of Experian, Barry Libenson, “It looks at ways to simplify the process, to reduce the amount of paper used and also to get to a decision much faster … with this new technology we should be able to get to a decision in a few days, rather than weeks, and potentially much faster than that.” Libenson goes on to say, “Over time we may find out we don’t need to care about five years of tax returns – but what we need is five years of credit payments.”
Rocket Mortgage and LoanDepot are other big names that are using machine learning for mortgage lending. LoanDepot recently partnered with artificial intelligence tool OJO Labs to bolster their end-to-end digital mortgage solution, Mello. OJO acts as an artificial intelligence personal assistant that communicates real estate information between a realtor and the consumer, learning from searches conducted by consumers to offer ever-changing advice.
Going forward, as more and more breakthroughs in artificial intelligence are created, mortgage companies and lenders will have to determine what technologies are applicable and relevant.
As machines become more capable of synthesizing large volumes of data, it will be interesting to see what information machines deem to be the most valuable regarding a borrower. For example, a New Jersey-based startup, Datanomers, has developed a “financial risk profiler” that uses artificial intelligence to search the web for unstructured non-financial data on loan applicants, indexes the information and generates a report for the underwriter. CEO of Datanomers, Deepak Dube explains; “There’s a wealth of information about people on the internet, but how do you extract the relevant information to complement the core financial data? That’s a major challenge that faces the financial industry at large.”
It is clear that artificial intelligence and machine learning will be a significant part of just about every financial industry. As the technology progresses, we will see just how impactful it can be in the mortgage industry.